Dissolved oxygen forecasting in the Mississippi River: advanced ensemble machine learning models
Francesco Granata, Senlin Zhu, Fabio Di Nunno
Abstract
This study introduces advanced ensemble machine learning models for predicting dissolved oxygen in the Mississippi River, offering high accuracy across various forecast horizons and improving environmental monitoring.
Topics & Concepts
Ensemble learningEnvironmental scienceComputer scienceArtificial intelligenceMachine learningHydrology (agriculture)MeteorologyEngineeringGeographyGeotechnical engineeringHydrological Forecasting Using AINeural Networks and ApplicationsWater Quality Monitoring Technologies